Abstract
Face recognition is one of the prominent biometric software applications, which can identify specific person in a digital image by analysing few parameters and comparing them. These type of recognitions are commonly used in security systems but are used increasingly in variety of other applications. Few non static conditions like facial hair can make recognition system a serious problem. The three stages of face recognition system are facing detection, feature extraction and classification. For enhancing the face recognition from video successions against dissimilar occlusion invariant and posture is proposed by using a novel approach. This face identification system made use of Viola and Jones algorithm for face detection and SURF (Speed Up Robust Feature) for feature extraction. Classifications of these face images are done using RBF (Radial Basis Function kernel) SVM (Support Vector Machine) classifier.
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References
K. Natarajan, J. Selvaganesan, Robust face recognition from video based on extensive feature set and fuzzy_bat algorithm. Indian J. Sci. Technol. 8(35) (2015)
P. Singh, J. Dalal, M.S. Meena, Person identification in a group photograph using surf features. Int. J. Innovations Adv. Comput. Sci. (IJIACS) 4(5) (2015)
W. Li, S. Shan, Z. Cui, X. Chen, in Fusing Robust Face Region Descriptors via Multiple Metric Learning for Face Recognition in the Wild (IEEE, 2013), pp. 3554–3561
S. Shankar Sastry, Z. Zhou, A.Y. Yang, L. Zhuang, in Single-Sample Face Recognition with Image Corruption and Misalignment via Sparse Illumination Transfer (IEEE, 2013), pp. 3546–3553
Y. Tian, Y. Shi, Z. Qi, Robust twin support vector machine for pattern classification. Elsevier 46, 305–316 (2013)
Y. Guo, M. Hayat, Y. Lie, M. Bennamoun, An efficient 3D face recognition approach using local geometrical signatures. Elsevier (2013)
G.J. Bala, S.L. Femandes, A novel technique to detect and recognize faces in multi-view videos. Recent Adv. Comput. Sci. (2015)
J. VijayaBarathi, E. Gurumoorthi, N. Nirosha, P. Sasikala, Identification of gender and face recognition using adaboost and SVM classifier. Int. J. Eng. Comput. Sci. 3(11) (2014)
P. Khatri, S. Agrawal, in Facial Expression Detection Techniques: Based on Viola and Jones algorithm and Principal Component Analysis (IEEE, 2015), pp. 108–112
Y. Liu, F. Guo, X. Luo, Research on feature extraction and match method based on the surf algorithm for mobile augmented reality system. Int. Ind. Inf. Comput. Eng. Conf. (IIICEC) (2015)
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Shwetha, S., Dixit, S., Khondanpur, B.I. (2017). Person Recognition Using Surf Features and Vola-Jones Algorithm. In: Satapathy, S., Bhateja, V., Udgata, S., Pattnaik, P. (eds) Proceedings of the 5th International Conference on Frontiers in Intelligent Computing: Theory and Applications . Advances in Intelligent Systems and Computing, vol 516. Springer, Singapore. https://doi.org/10.1007/978-981-10-3156-4_56
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DOI: https://doi.org/10.1007/978-981-10-3156-4_56
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